Fig 2: Characterizing heterogeneity within lymphoid populations(A) Mutually exclusive expression of the integrin proteins CD103 and CD49a within CD8+ T memory cells, as measured by CITE-seq.(B) Differential expression of integrin-7 between CD103+ CD49a- and CD103+ CD49+ populations as measured by CITE-seq.(C and D) Flow cytometry validates the presence of these populations. Plots are the same as in (A) and (B) but generated via flow cytometry.(E and F) Differentially expressed genes, and enriched gene ontology terms, between CD103+ CD49a- and CD103- CD49+ populations.(G) Dot plot showing the representation of the fifteen most abundant T cell clonotypes in the dataset. For space, only the VDJ regions are shown on the y axis, but all cells in a clone share identical CDR3 sequences. Clones reside in a restricted set of cytotoxic and effector cell states and are shared across vaccination time points. Size of each dot represents the number of cells in the clonotype. Clones present in donors who were classified as CMV-positive are colored in red.(H) Cells within a clone exhibit similar molecular profiles. Grey dots represent T cells where TCR sequence was measured using the 10x 5' assay. Cells from the eight most highly represented clonotypes are highlighted as colored dots.(I–K) Heterogeneity in NK cells is defined by two gradients correlating with CD16 and CD38 protein expression. (I) NK cells are ordered by their quantitative expression of CD16 protein expression. Rolling averages for the expression of genes that correlate positively or negatively with CD16 are shown as smoothed lines. (J) same as (I) but for CD38. (K) CD38 and CD16 protein expression define two separate gradients and are uncorrelated in NK cells.See also Figure S5 and Table S3.

Fig 3: Identification and phenotypic characterization of human liver-type ILC1s(A) CITE-seq analysis (protein) of hepatic Lin-CD45+ lymphocytes showing relative expression of CD49a, CD94, and NKp80 in the LT-ILC1 cluster illustrated in UMAP (only batch 2).(B) Relative expression levels of the indicated markers among each of the indicated populations as measured by CITE-seq analysis (only batch 2).(C) PhenoGraph cluster analysis of flow cytometry data from hepatic Lin-CD45+ lymphocytes displayed in UMAP. Clustering and UMAP is based on following markers: CD94, CD45, CD56, CD117, CD52, CD200R1, CRTH2, T-BET, NKp80, CD161, CD49a, EOMES, CXCR6, and CD127.(D) Heatmap showing the relative expression of the indicated markers from nine PhenoGraph clusters identified in (C) as measured by flow cytometry and calculated to a Z score for each marker.(E) Representative flow cytometry plots showing the gating strategy from singlet Lin-CD45+ lymphocytes (from healthy livers) to identify liver-type (LT)-ILC1 (pink), cNK (turquoise), CD49a+trNK cells (violet), CD49a-trNK cells (red), classical (c) ILC1 (gray), ILC2 (blue), and ILC3 (green) populations.(F) PhenoGraph cluster analysis of flow cytometry data from hepatic Lin-CD45+ lymphocytes with assignment of the indicated populations.(G) Representative histograms showing the relative expression of the indicated markers in each identified population to distinguish ILCs from NK cell populations.(H) Representative histograms showing the relative expression of the indicated markers in each identified population, each of which is elevated on LT-ILC1.See Figure S2.

Fig 4: Additional heterogeneity within lymphoid populations, related to Figure 5(A) Protein expression of canonical resident lymphocyte marker CD69 in CD8+ CD103+, CD8+ CD49a+ T cell populations. Neither population is positive. Platelets are included as a positive control, as CD69 is constitutively expressed on these cells. (B) Naive, intermediate and memory B cells are ordered by their quantitative level of CD27 protein expression. Rolling averages for the expression of genes that correlate positively or negatively with CD27 are shown as smoothed lines. (C-E) Same as Figure 5J, but after splitting the eight volunteers into five CMV+ (C) and three CMV- (D) samples (Table S3). We observe concordant trends in both subsets, as well as an independent CITE-seq dataset (Kotliarov et al., 2020). (F) UMAP visualization of CITE-seq dataset of 49,147 PBMC analyzed with the 10X 5' Immune Profiling kit, which also measures immune repertoires. The dataset has been mapped onto the 3'-defined multimodal reference, allowing cells to be visualized in the same UMAP space as the reference, and cells are labeled based on transferred Level 2 annotations. (G) Dot plot showing the overrepresentation of TCRa sequences within cells annotated as MAIT. As expected, we detect the canonical MAIT TRAV1-2-TRAJ33 as the most abundant sequence along with reduced usage of TRAJ12 and TRAJ20. We also detect rare populations of invariant NKT cells (defined by the use of TRAV10.TRAJ18). As expected, and in contrast to the clonotypes reported in Figure 5G, these findings are consistent across volunteers, vaccination time points, and CMV status.

Fig 5: Liver-type ILC1s are increased in cirrhotic liver tissues(A) Comparison of LT-ILC1 (Lin-CD45+CD94+NKp80-CD200R1+CD49a+) frequencies calculated as percentages among total Lin- lymphocytes between control livers (perfusate n = 7), control livers (non-perfusate; n = 8), and cirrhotic livers (n = 29) (patient characteristics shown in Table S2).(B) Correlation matrix estimated for LT-ILC1s (percent of Lin-), age, AST, ALT, gamma-GT, total bilirubin, MELD score (Model of End Stage Liver Disease), IFNG (mRNA), IL13 (mRNA), IL1B (mRNA), IL2 (mRNA), IL7 (mRNA), and TGFB1 (mRNA). LT-ILC1 frequencies were obtained from 25 cirrhotic livers. Spearman correlation coefficients (R) are given as color code. Statistically significant correlations are indicated with *p < 0.05, **p < 0.01, ***p < 0.001.(C) Representative expression of the indicated markers by human LT-ILC1 (pink), cNK cells (turquoise), CD49a+trNK cells (violet), CD49a-trNK cells (red), cILC1s (gray), ILC2s (blue), and ILC3s (green), comparing populations derived from healthy and cirrhotic livers. Data are representative of at least three independent experiments.(D) Comparison of IFN-? production (healthy, n = 7; cirrhotic, n = 9), IL-2 production (healthy, n = 4; cirrhotic, n = 4), CD107a degranulation (healthy, n = 3; cirrhotic, n = 5), TNF-a production (healthy, n = 7; cirrhotic, n = 5), and GM-CSF production (healthy, n = 4; cirrhotic, n = 3) between healthy and cirrhotic livers related to LT-ILC1 (pink), cNK cells (turquoise), CD49a+trNK cells (violet), CD49a-trNK cells (red), and ILC3s (green), from healthy and cirrhotic livers following 5 h PMA and ionomycin stimulation and measured by intracellular flow cytometry.(E) Volcano plot showing DEG differences based on scRNA-seq data between LT-ILC1s comparing “control versus cirrhotic liver tissues” from batch 2.*p < 0.05, ***p < 0.001, error bars represent SEM. See Figure S4.